AWS Big Data

APRIL 3, 2024

They understand that a one-size-fits-all approach no longer works, and recognize the value in adopting scalable, flexible tools and open data formats to support interoperability in a modern data architecture to accelerate the delivery of new solutions.

Data Lake 97

Data Lake Snapshot Metadata Data Architecture 97

Data Virtualization

MARCH 28, 2024

As noted in the Gartner Hype Cycle for Finance Data and Analytics Governance, 2023, “Through. The post My Understanding of the Gartner® Hype Cycle™ for Finance Data and Analytics Governance, 2023 appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Finance 69

Finance Digital Transformation Analytics Data Integration 69

Ontotext

APRIL 10, 2024

In most enterprises data teams lack a data map and data asset inventory and are often unaware of data that exists across the organization, its associated profile, quality and associated metadata. Teams can’t access data to build their business use cases. For example, a product data tag is basic metadata.

Metadata 52

Metadata Data Lake Data Warehouse Data Quality 52

AWS Big Data

OCTOBER 3, 2023

You can store your data as-is, without having to first structure the data and then run different types of analytics for better business insights. Analytics use cases on data lakes are always evolving. In this method, the metadata are recreated in an isolated environment and colocated with the existing data files.

Data Lake 105

Data Lake Metadata Snapshot Recreation/Entertainment 105

Ontotext

AUGUST 22, 2023

The age of Big Data inevitably brought computationally intensive problems to the enterprise. Central to today’s efficient business operations are the activities of data capturing and storage, search, sharing, and data analytics. With semantic metadata, enterprise data gets linked to one another and to external sources.

Metadata 52

Metadata Knowledge Discovery Big Data Enterprise 52

AWS Big Data

DECEMBER 13, 2023

In addition to using native managed AWS services that BMS didn’t need to worry about upgrading, BMS was looking to offer an ETL service to non-technical business users that could visually compose data transformation workflows and seamlessly run them on the AWS Glue Apache Spark-based serverless data integration engine.

Metadata 90

Metadata Data Lake Visualization Data Transformation 90

DataKitchen

OCTOBER 20, 2023

In today’s data-driven landscape, Data and Analytics Teams i ncreasingly face a unique set of challenges presented by Demanding Data Consumers who require a personalized level of Data Observability.

Insurance 176

Insurance Metadata Data-driven Data Quality 176

CIO Business Intelligence

MARCH 4, 2024

Stakeholders are currently waging an open debate across the industry of centralization versus federated data strategies. Proponents of centralization continue to assert its effectiveness in driving operational efficiencies, enhancing analytics effectiveness, and enabling governance crucial to data security, privacy, and regulatory compliance.

Insurance 98

Insurance Strategy Data Governance Data Integration 98

CIO Business Intelligence

MARCH 24, 2023

The program must introduce and support standardization of enterprise data. Programs must support proactive and reactive change management activities for reference data values and the structure/use of master data and metadata. One of its key capabilities, TrustCheck, provides real-time “guardrails” to workflows.

Data Governance 142

Data Governance Management Metadata Data Quality 142

AWS Big Data

APRIL 29, 2024

Addressing big data challenges – Big data comes with unique challenges, like managing large volumes of rapidly evolving data across multiple platforms. Effective permission management helps tackle these challenges by controlling how data is accessed and used, providing data integrity and minimizing the risk of data breaches.

Management 98

Management Big Data Metadata Data Warehouse 98

Rocket-Powered Data Science

JULY 6, 2021

This is accomplished through tags, annotations, and metadata (TAM). granules) of the data collection for fast search, access, and retrieval is also important for efficient orchestration and delivery of the data that fuels AI, automation, and machine learning operations. Collect, curate, and catalog (i.e.,

Strategy 266

Strategy Machine Learning Metadata Knowledge Discovery 266

AWS Big Data

FEBRUARY 29, 2024

However, enterprise data generated from siloed sources combined with the lack of a data integration strategy creates challenges for provisioning the data for generative AI applications. Data discoverability Unlike structured data, which is managed in well-defined rows and columns, unstructured data is stored as objects.

Data Governance 98

Data Governance Unstructured Data Metadata Data Lake 98

erwin

JANUARY 9, 2020

That’s because it’s the best way to visualize metadata , and metadata is now the heart of enterprise data management and data governance/ intelligence efforts. So here’s why data modeling is so critical to data governance. erwin Data Modeler: Where the Magic Happens.

Data Governance 144

Data Governance Modeling Metadata Unstructured Data 144

Smart Data Collective

JULY 15, 2021

A data catalog serves the same purpose. By using metadata (or short descriptions), data catalogs help companies gather, organize, retrieve, and manage information. You can think of a data catalog as an enhanced Access database or library card catalog system. What Does a Data Catalog Do?

Metadata 127

Metadata IT Data-driven Data Quality 127

Ontotext

DECEMBER 1, 2023

So, KGF 2023 proved to be a breath of fresh air for anyone interested in topics like data mesh and data fabric , knowledge graphs, text analysis , large language model (LLM) integrations, retrieval augmented generation (RAG), chatbots, semantic data integration , and ontology building.

Metadata 78

Metadata Sales Consulting Enterprise 78

erwin

JANUARY 30, 2020

1 reason to implement data governance. However, the latest group of survey participants say better decision-making is their primary driver (62 percent), with analytics secondary (51 percent), and regulatory compliance coming in third (48 percent). And close to 50 percent have deployed data catalogs and business glossaries.

Data Governance 145

Data Governance Metadata Cost-Benefit Digital Transformation 145

O'Reilly on Data

JANUARY 29, 2019

Companies are building or evaluating solutions in foundational technologies needed to sustain success in analytics and AI.

Deep Learning 208

Deep Learning Machine Learning Data Science Metadata 208

Ontotext

SEPTEMBER 15, 2020

Added to this is the increasing demands being made on our data from event-driven and real-time requirements, the rise of business-led use and understanding of data, and the move toward automation of data integration, data and service-level management. Knowledge Graphs are the Warp and Weft of a Data Fabric.

Metadata 69

Metadata Knowledge Discovery Data Quality Strategy 69

Cloudera

FEBRUARY 11, 2019

The January 2019 “Magic Quadrant for Data Management Solutions for Analytics” provides valuable insights into the status, direction, and players in the DMSA market. All this while the platform serves as the core foundation providing metadata and governance capabilities across these workloads.

Management 43

Management Metadata Analytics Machine Learning 43

IBM Big Data Hub

NOVEMBER 4, 2022

This complements IBM’s partnership with MANTA to integrate automated data lineage capabilities from MANTA with IBM Watson Knowledge Catalog on Cloud Pak for Data. Why does data quality matter across the data lifecycle? Data quality issues can have far-reaching consequences across the lifecycle of data: 1.

Data Quality 57

Data Quality Metadata Data Governance Data-driven 57

IBM Big Data Hub

APRIL 9, 2018

There’s a general need for next-gen executives to not only understand corporate regulations, but be able to adhere to and follow them using metadata solutions like data governance. As the business world’s top asset becomes data, data governance will ensure that data and information being handled is consistent, reliable and trustworthy.

Data Governance 96

Data Governance Metadata Data Integration Analytics 96

CIO Business Intelligence

OCTOBER 26, 2023

Business intelligence (BI) analysts transform data into insights that drive business value. Business intelligence analyst job requirements BI analysts typically handle analysis and data modeling design using data collected in a centralized data warehouse or multiple databases throughout the organization.

Business Intelligence 126

Business Intelligence Data-driven Statistics Data Warehouse 126

IBM Big Data Hub

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

Ontotext

JANUARY 26, 2023

The catalog stores the asset’s metadata in RDF. This allows keeping a well-defined representation of the metadata of each asset and enables using a SPARQL endpoint to query it. Towards that end authors introduce a system for integrity checks for building automation applications and using more reliable data for data analytics processes.

Interactive 52

Interactive Metadata Data Integration Data-driven 52

Ontotext

NOVEMBER 4, 2021

Due to the huge value generated by their data standardization and semantic modeling capabilities, knowledge graphs are most often associated with data integration, linking, unification and information reuse. But these tasks are only part of the story. In two of its 9.x

Metadata 98

Metadata Visualization Modeling Enterprise 98

erwin

JANUARY 17, 2020

Data modeling is a process that enables organizations to discover, design, visualize, standardize and deploy high-quality data assets through an intuitive, graphical interface. Data models provide visualization, create additional metadata and standardize data design across the enterprise. SQL or NoSQL?

Data-driven 138

Data-driven Modeling Metadata Data Governance 138

Ontotext

JULY 13, 2023

For example, offering more of the same product or content instead of complementary items Analytics tools that don’t really support decision making Chatbots that fail the Alan Turing test You name it! Enterprises generate an enormous amount of data and content every minute. How can you build knowledge graphs for enterprise applications?

Enterprise 52

Enterprise Metadata Digital Transformation Software 52

erwin

APRIL 29, 2020

Many large organizations, in their desire to modernize with technology, have acquired several different systems with various data entry points and transformation rules for data as it moves into and across the organization. Who are the data owners? Data lineage offers proof that the data provided is reflected accurately.

Metadata 111

Metadata Data Governance Key Performance Indicator Data Quality 111

Octopai

JUNE 1, 2020

Data mapping is the cornerstone of many important business intelligence processes: Data Integration – Even if systems are compatible, combining two disparate data repositories still requires meticulous data mapping. Enforcing finance regulations has also become a concern for BI & analytics teams.

Metadata 52

Metadata Data Warehouse Data Integration Finance 52

Ontotext

AUGUST 5, 2020

Each of the four FAIR principles calls for data and metadata to be easily found, accessed, understood, exchanged and reused. FAIR data is data that is: Findable is such data in which data and metadata are assigned a globally unique and persistent identifier so that computers can easily find it.

Metadata 52

Metadata Insurance Manufacturing Data Integration 52

IBM Big Data Hub

JANUARY 5, 2023

Both approaches were typically monolithic and centralized architectures organized around mechanical functions of data ingestion, processing, cleansing, aggregation, and serving. Monitor and identify data quality issues closer to the source to mitigate the potential impact on downstream processes or workloads.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

erwin

FEBRUARY 19, 2021

Metadata management is key to wringing all the value possible from data assets. However, most organizations don’t use all the data at their disposal to reach deeper conclusions about how to drive revenue, achieve regulatory compliance or accomplish other strategic objectives. What Is Metadata? Harvest data.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

IBM Big Data Hub

JULY 13, 2023

When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data. Together, these factors determine the reliability of the organization’s data. In short, yes.

Data Quality 70

Data Quality Data Integration Metadata Cost-Benefit 70

AWS Big Data

MARCH 29, 2024

You can slice data by different dimensions like job name, see anomalies, and share reports securely across your organization. With these insights, teams have the visibility to make data integration pipelines more efficient. An AWS Glue crawler scans data on the S3 bucket and populates table metadata on the AWS Glue Data Catalog.

Metrics 108

Metrics Visualization Dashboards Interactive 108

Cloudera

AUGUST 31, 2021

Data warehousing is the backbone of every data driven organization , providing mission critical analytics. Today, modern data warehousing has evolved to meet the intensive demands of the newest analytics required for a business to be data driven. Copyright © 2021 Accenture. All rights reserved.

Data Warehouse 81

Data Warehouse Cost-Benefit Metadata Data-driven 81

AWS Big Data

JUNE 7, 2023

This data needs to be ingested into a data lake, transformed, and made available for analytics, machine learning (ML), and visualization. For this, Cargotec built an Amazon Simple Storage Service (Amazon S3) data lake and cataloged the data assets in AWS Glue Data Catalog.

Metadata 56

Metadata Data Lake Machine Learning Big Data 56

AWS Big Data

AUGUST 15, 2023

As customers accelerate their migrations to the cloud and transform their businesses, some find themselves in situations where they have to manage data analytics in a multi-cloud environment, such as acquiring a company that runs on a different cloud provider. We use Athena to run queries on data stored on Google Cloud Storage.

Recreation/Entertainment 88

Recreation/Entertainment Unstructured Data Business Intelligence Data-driven 88